Coherent, super-resolved radar beamforming using self-supervised learning-Reference-Cited by-同舟云学术

Coherent, super-resolved radar beamforming using self-supervised learning

Published:2021-12-15 Issue:61 Volume:6 Page:
ISSN:2470-9476
Container-title:Science Robotics
language:en
Short-container-title:Sci. Robot.

Author:

Orr Itai¹²^ORCID,Cohen Moshik²,Damari Harel²^ORCID,Halachmi Meir²^ORCID,Raifel Mark²,Zalevsky Zeev¹

Affiliation:

1. Faculty of Engineering and the Institute for Nanotechnology and Advanced Materials, Bar Ilan University, Ramat-Gan, Israel.

2. Wisense Technologies Ltd., Tel Aviv, Israel.

Abstract

Self-supervised training of deep neural networks in unstructured environments enables enhanced angular resolution in radar systems.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Mechanical Engineering

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4. International Organization for Standardization ISO 26262-1:2018 (2018); www.iso.org/standard/68383.html.

5. Super Resolution Wide Aperture Automotive Radar

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